Abstract
Alzheimers disease [AD] is the most common cause of dementia in North America. Despite 30+ years of intense investigation, the field lacks consensus regarding the etiology and pathogenesis of sporadic AD, and therefore we still do not know the best strategies for treating and preventing this debilitating and costly disease. However, growing evidence supports the concept that AD is fundamentally a metabolic disease with substantial and progressive derangements in brain glucose utilization and responsiveness to insulin and insulin-like growth factor [IGF] stimulation. Moreover, AD is now recognized to be heterogeneous in nature, and not solely the end-product of aberrantly processed, misfolded, and aggregated oligomeric amyloid-beta peptides and hyperphosphorylated tau. Other factors, including impairments in energy metabolism, increased oxidative stress, inflammation, insulin and IGF resistance, and insulin/IGF deficiency in the brain should be incorporated into all equations used to develop diagnostic and therapeutic approaches to AD. Herein, the contributions of impaired insulin and IGF signaling to AD-associated neuronal loss, synaptic disconnection, tau hyperphosphorylation, amyloid-beta accumulation, and impaired energy metabolism are reviewed. In addition, we discuss current therapeutic strategies and suggest additional approaches based on the hypothesis that AD is principally a metabolic disease similar to diabetes mellitus. Ultimately, our ability to effectively detect, monitor, treat, and prevent AD will require more efficient, accurate and integrative diagnostic tools that utilize clinical, neuroimaging, biochemical, and molecular biomarker data. Finally, it is imperative that future therapeutic strategies for AD abandon the concept of uni-modal therapy in favor of multi-modal treatments that target distinct impairments at different levels within the brain insulin/IGF signaling cascades.
Keywords: Alzheimer's disease, dementia, neurofibrillary tangles, neurodegeneration cascade, hyperphosphorylated tau, energy metabolism, endoplasmic reticulum, neurotoxic, neuro-imaging
Current Alzheimer Research
Title: Brain Insulin Resistance and Deficiency as Therapeutic Targets in Alzheimers Disease
Volume: 9 Issue: 1
Author(s): Suzanne M. de la Monte
Affiliation:
Keywords: Alzheimer's disease, dementia, neurofibrillary tangles, neurodegeneration cascade, hyperphosphorylated tau, energy metabolism, endoplasmic reticulum, neurotoxic, neuro-imaging
Abstract: Alzheimers disease [AD] is the most common cause of dementia in North America. Despite 30+ years of intense investigation, the field lacks consensus regarding the etiology and pathogenesis of sporadic AD, and therefore we still do not know the best strategies for treating and preventing this debilitating and costly disease. However, growing evidence supports the concept that AD is fundamentally a metabolic disease with substantial and progressive derangements in brain glucose utilization and responsiveness to insulin and insulin-like growth factor [IGF] stimulation. Moreover, AD is now recognized to be heterogeneous in nature, and not solely the end-product of aberrantly processed, misfolded, and aggregated oligomeric amyloid-beta peptides and hyperphosphorylated tau. Other factors, including impairments in energy metabolism, increased oxidative stress, inflammation, insulin and IGF resistance, and insulin/IGF deficiency in the brain should be incorporated into all equations used to develop diagnostic and therapeutic approaches to AD. Herein, the contributions of impaired insulin and IGF signaling to AD-associated neuronal loss, synaptic disconnection, tau hyperphosphorylation, amyloid-beta accumulation, and impaired energy metabolism are reviewed. In addition, we discuss current therapeutic strategies and suggest additional approaches based on the hypothesis that AD is principally a metabolic disease similar to diabetes mellitus. Ultimately, our ability to effectively detect, monitor, treat, and prevent AD will require more efficient, accurate and integrative diagnostic tools that utilize clinical, neuroimaging, biochemical, and molecular biomarker data. Finally, it is imperative that future therapeutic strategies for AD abandon the concept of uni-modal therapy in favor of multi-modal treatments that target distinct impairments at different levels within the brain insulin/IGF signaling cascades.
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Cite this article as:
M. de la Monte Suzanne, Brain Insulin Resistance and Deficiency as Therapeutic Targets in Alzheimers Disease, Current Alzheimer Research 2012; 9 (1) . https://dx.doi.org/10.2174/156720512799015037
DOI https://dx.doi.org/10.2174/156720512799015037 |
Print ISSN 1567-2050 |
Publisher Name Bentham Science Publisher |
Online ISSN 1875-5828 |
Call for Papers in Thematic Issues
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Aims and Scope: Introduction: Alzheimer's disease (AD) poses a significant global health challenge, with an increasing prevalence that demands concerted efforts to advance our understanding and strategies for prevention, diagnosis, treatment, and rehabilitation. This thematic issue aims to bring together cutting-edge research and innovative approaches from multidisciplinary perspectives to address ...read more
Alzheimer's Disease Drug Development
Alzheimer's disease is a progressive neurodegenerative disorder that affects millions of people worldwide. Despite decades of research, no cure or disease-modifying treatment is available yet. Therefore, the need for developing effective therapies to treat Alzheimer's disease is an urgent matter. This special issue aims to provide a comprehensive overview of ...read more
Current updates on the Role of Neuroinflammation in Neurodegenerative Disorders
Neuroinflammation is an invariable hallmark of chronic and acute neurodegenerative disorders and has long been considered a potential drug target for Alzheimer?s disease (AD) and dementia. Significant evidence of inflammatory processes as a feature of AD is provided by the presence of inflammatory markers in plasma, CSF and postmortem brain ...read more
Deep Learning for Advancing Alzheimer's Disease Research
Alzheimer's disease (AD) poses a significant global health challenge, with an increasing number of individuals affected yearly. Deep learning, a subfield of artificial intelligence, has shown immense potential in various domains, including healthcare. This thematic issue of Current Alzheimer Research explores the application of deep learning techniques in advancing our ...read more
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